Kenaf (<i>Hibiscus Cannabinus</i> L.) Breeding

Afzal, Muhammad; Ibrahim, Aminu; Xu, Yi; Niyitanga, Sylvain; Yi, Li; Li, Dongxu

doi:10.1080/15440478.2020.1852998

Cited by 13 publications

(8 citation statements)

References 79 publications

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“…Kenaf (Hibiscus cannabinus L.) is an important industrial crop worldwide [ 1 ]. The total area in the world for kenaf, jute ( Corchorus olitorius ), and allied fiber were 1.50 mha, with a total annual production of 3.38 million tonnes in 2019 ( http://www.fao.org/faostat/en/#data/QC ).…”

Section: Introductionmentioning

confidence: 99%

RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.)

et al. 2021

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Kenaf (Hibiscus cannabinus L.) is an industrial crop used as a raw material in various fields and is cultivated worldwide. Compared to high potential for its utilization, breeding sector is not vigorous partially due to laborous breeding procedure. Thus, efficient breeding methods are required for varieties that can adapt to various environments and obtain optimal production. For that, identifying kenaf’s characteristics is very important during the breeding process. Here, we investigated if RGB based vegetative index (VI) could be associated with traits for biomass. We used 20 varieties and germplasm of kenaf and RGB images taken with unmanned aerial vehicles (UAVs) for field selection in early and late growth stage. In addition, measuring the stem diameter and the number of nodes confirmed whether the vegetative index value obtained from the RGB image could infer the actual plant biomass. Based on the results, it was confirmed that the individual surface area and estimated plant height, which were identified from the RGB image, had positive correlations with the stem diameter and node number, which are actual growth indicators of the rate of growth further, biomass could also be estimated based on this. Moreover, it is suggested that VIs have a high correlation with actual growth indicators; thus, the biomass of kenaf could be predicted. Interstingly, those traits showing high correlation in the late stage had very low correlations in the early stage. To sum up, the results in the current study suggest a more efficient breeding method by reducing labor and resources required for breeding selection by the use of RGB image analysis obtained by UAV. This means that considerable high-quality research could be performed even with a tight budget. Furthermore, this method could be applied to crop management, which is done with other vegetative indices using a multispectral camera.

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Section: Introductionmentioning

confidence: 99%

RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.)

et al. 2021

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“…The skewness of all four traits was close to zero, and the height of the distribution was lower than the normal distribution. Ivory was the most common flower color (55 lines), followed by white (25) and purple (1). The most common stem color was green (89 lines), followed by dark purple (6) and brown (1).…”

Section: Phenotypic Variation and Correlation Analysismentioning

confidence: 99%

“…Ivory was the most common flower color (55 lines), followed by white (25) and purple (1). The most common stem color was green (89 lines), followed by dark purple (6) and brown (1). For leaf shape, there were 53 palmate types and 43 entire types.…”

Section: Phenotypic Variation and Correlation Analysismentioning

confidence: 99%

“…A member of the Malvaceae family, kenaf (Hibiscus cannabinus L.), is a diploid (2n = 2X = 36) annual herbaceous plant native to Africa [1]. Originating in North Africa, kenaf is now cultivated in many countries, including India, Russia, China, and the United States, and is known to thrive in temperate and tropical environments with abundant sunlight and precipitation [1,2]. Kenaf has a variety of valuable industrial uses, including as a source of edible seed oil, stem fiber, plastic raw materials, and pharmaceuticals.…”

Section: Introductionmentioning

confidence: 99%

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Genome-Wide Association Study for Agronomic Traits in Gamma-Ray-Derived Mutant Kenaf (Hibiscus cannabinus L.)

Kim,

Yang,

Lee

et al. 2024

Plants

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Kenaf (Hibiscus cannabinus L.), in the Malvaceae family, is an important crop for not only fiber production, but also various other industrial materials. We performed phylogenetic analysis and a genome-wide association study (GWAS) of seven agronomic traits: days to flowering, plant height, fresh weight, dry weight, flower color, stem color, and leaf shape, using 96 kenaf genotypes, including gamma-irradiation-derived mutant lines. Genotypes were determined by genotyping-by-sequencing (GBS) and a total of 49,241 single-nucleotide polymorphisms (SNPs) were used in the analysis. Days to flowering, plant height, fresh weight, and dry weight were positively correlated with each other, and stem color was also correlated with fresh weight and dry weight. The phylogenetic analysis divided the 96 lines into nine related groups within two independent groups, and the GWAS analysis detected a total of 49 SNPs for days to flowering, plant height, fresh weight, dry weight, flower color, stem color, and leaf shape with −log10(P) ≥ 4, of which 22 were located in genic regions. The detected SNPs were located in genes with homology ranging from 45% to 96% to plants of the Malvaceae and Betulaceae, and these genes were found to be involved in plant growth and development via various pathways. Our identification of SNP markers related to agronomic traits is expected to help improve the quality of selective breeding programs for kenaf.

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“…Kenaf is cultivated worldwide due to its adaptability to various climates and soil types. The usefulness of kenaf in industry and agriculture is attributed to its fibrous stems, functional compounds, and, especially, its high crude protein content [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity Assessment of Kenaf Breeding Field through Spatial Dependence Analysis on Crop Growth Status Map Derived by Unmanned Aerial Vehicle

Jang

Kim

Park

et al. 2023

Plants

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The investigation of quantitative phenotypic traits resulting from the interaction between targeted genotypic traits and environmental factors is essential for breeding selection. Therefore, plot-wise controlled environmental factors must be invariable for accurate identification of phenotypes. However, the assumption of homogeneous variables within the open-field is not always accepted, and requires a spatial dependence analysis to determine whether site-specific environmental factors exist. In this study, spatial dependence within the kenaf breeding field was assessed in a geo-tagged height map derived from an unmanned aerial vehicle (UAV). Local indicators of spatial autocorrelation (LISA) were applied to the height map using Geoda software, and the LISA map was generated in order to recognize the existence of kenaf height status clusters. The spatial dependence of the breeding field used in this study appeared in a specific region. The cluster pattern was similar to the terrain elevation pattern of this field and highly correlated with drainage capacity. The cluster pattern could be utilized to design random blocks based on regions that have similar spatial dependence. We confirmed the potential of spatial dependence analysis on a crop growth status map, derived by UAV, for breeding strategy design with a tight budget.

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Kenaf (Hibiscus Cannabinus L.) Breeding

Cited by 13 publications

References 79 publications

RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.)

RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.)

Genome-Wide Association Study for Agronomic Traits in Gamma-Ray-Derived Mutant Kenaf (Hibiscus cannabinus L.)

Heterogeneity Assessment of Kenaf Breeding Field through Spatial Dependence Analysis on Crop Growth Status Map Derived by Unmanned Aerial Vehicle

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